An artificial intelligence perspective: How knowledge and confidence shape risk and benefit perception

Said, Nadia; Potinteu, Andreea Elena; Brich, Irina; Buder, Jürgen; Schumm, Hanna; Huff, Markus

doi:10.1016/j.chb.2023.107855

Cited by 12 publications

(11 citation statements)

References 108 publications

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“…Note, that our focus is to investigate whether risk and benefit perception differs for laypeople as opposed to medical staff. As has been shown in other research, AI expertise is related to higher expected benefits (Araujo et al, 2019) and higher accurate knowledge about AI generally is related to a lower risk perception of artificial intelligence (Said et al, 2023). Given those results we will control for AI knowledge in all models.…”

Section: The Present Studymentioning

confidence: 84%

“…AI Knowledge and Confidence in AI Knowledge. In their study, Said et al (2023) showed that, aside from peoples' attitudes towards AI, knowledge about AI and confidence in knowledge about AI are important predictors for peoples' AI risk and benefit perception. More specifically, results showed that higher AI knowledge was related to lower risk perceptions, while higher confidence in AI knowledge was related to a higher benefit perception of artificial intelligence.…”

Section: Risk and Benefit Perception Of Artificial Intelligencementioning

confidence: 99%

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Artificial Intelligence in Medicine: The Influence of Medical Expertise and Perceived Causability on Medical AI Risk and Benefit Perception

Said,

Schumacher,

Huff

2023

Preprint

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Artificial intelligence (AI) is increasingly used in medicine, making it one of the largest and fastest-growing fields in which AI is applied. While some AI-based applications are already outperforming experts regarding diagnostic accuracy, patients’ trust in AI is still comparatively low. Given the tremendous potential of medical AI applications, understanding what influences patients’ and doctors’ perceptions of medical AI is of utmost importance. To this end, we assessed for N = 750 participants (N = 684 laypeople and N = 66 medical experts) whether medical expertise and perceived causability, that is the transparency, efficiency and satisfaction with which the AI is perceived, are related to the perception of risks and benefits in three different medical AI scenarios. Benefit perception increased with higher perceived causability but was unrelated to medical expertise. On the other hand, risk perception increased with higher medical expertise and decreased with higher perceived causability. Therefore, when introducing and using medical AI applications in the treatment of patients, it is essential to sensitize both patients and medical experts to the different perceptions. Such measures can be an important prerequisite for increasing AI acceptance in medicine.

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Section: The Present Studymentioning

confidence: 84%

Section: Risk and Benefit Perception Of Artificial Intelligencementioning

confidence: 99%

Artificial Intelligence in Medicine: The Influence of Medical Expertise and Perceived Causability on Medical AI Risk and Benefit Perception

Said,

Schumacher,

Huff

2023

Preprint

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“…At this point in Study 2, a knowledge test about ATG followed. The test covered 15 partly adapted [46] statements, for which participants had to decide whether they were true, false, or if they didn't know (e.g., "Humans can still easily recognize AI-generated speech as artificial speech").…”

Section: Measures and Proceduresmentioning

confidence: 99%

Understanding and Perception of Automated Text Generation among the Public: Two Surveys with Representative Samples in Germany

Lermann Henestrosa,

Kimmerle

2024

Behavioral Sciences

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Automated text generation (ATG) technology has evolved rapidly in the last several years, enabling the spread of content produced by artificial intelligence (AI). In addition, with the release of ChatGPT, virtually everyone can now create naturally sounding text on any topic. To optimize future use and understand how humans interact with these technologies, it is essential to capture people’s attitudes and beliefs. However, research on ATG perception is lacking. Based on two representative surveys (March 2022: n1 = 1028; July 2023: n2 = 1013), we aimed to examine the German population’s concepts of and attitudes toward AI authorship. The results revealed a preference for human authorship across a wide range of topics and a lack of knowledge concerning the function, data sources, and responsibilities of ATG. Using multiple regression analysis with k-fold cross-validation, we identified people’s attitude toward using ATG, performance expectancy, general attitudes toward AI, and lay attitude toward ChatGPT and ATG as significant predictors of the intention to read AI-written texts in the future. Despite the release of ChatGPT, we observed stability across most variables and minor differences between the two survey points regarding concepts about ATG. We discuss the findings against the backdrop of the ever-increasing availability of automated content and the need for an intensive societal debate about its chances and limitations.

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“…At this point in Study 2, a knowledge test about ATG followed. The test covered 15 partly adapted [44] statements, for which participants had to decide whether they were true, false, or if they didn't know (e.g., "Humans can still easily recognize AI-generated speech as artificial speech").…”

Section: Measures and Proceduresmentioning

confidence: 99%

Understanding and Perception of Automated Text Generation among the Public: Two Surveys with Representative Samples in Germany

Henestrosa,

Kimmerle

2023

Preprint

View full text Add to dashboard Cite

The application of automated text generation (ATG) technology has evolved rapidly in the last several years, leading to more available content being produced by artificial intelligence (AI). With the release of ChatGPT in November 2022, a tool is now at hand that allows virtually everyone to create naturally sounding text on any topic. However, research on public beliefs about and attitudes toward ATG is lacking. Two surveys with representative samples (n1 = 1,028, n2 = 1,013) examined the German population’s concepts of and attitudes toward AI authorship in 2022 and 2023. The results revealed a preference for human authorship across a wide range of topics and a lack of knowledge concerning the function, data sources, and responsibilities of ATG. Using multiple regression analysis with k-fold cross-validation, we identified several significant predictors of the intention to read AI-written texts in the future. Despite the release of ChatGPT, we observed stability across most variables and minor differences between the two survey points regarding concepts about ATG. We discuss the findings against the backdrop of the ever-increasing availability of automated content and the need for an intensive societal debate about the chances and limitations of this technology.

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An artificial intelligence perspective: How knowledge and confidence shape risk and benefit perception

Cited by 12 publications

References 108 publications

Artificial Intelligence in Medicine: The Influence of Medical Expertise and Perceived Causability on Medical AI Risk and Benefit Perception

Artificial Intelligence in Medicine: The Influence of Medical Expertise and Perceived Causability on Medical AI Risk and Benefit Perception

Understanding and Perception of Automated Text Generation among the Public: Two Surveys with Representative Samples in Germany

Understanding and Perception of Automated Text Generation among the Public: Two Surveys with Representative Samples in Germany

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